Map data for electronic navigation devices, such as GPS based personal navigation devices like the GO™ from TomTom International BV, comes from specialist map vendors. Such devices are also referred to as Portable Navigation Devices (PND's). This map data is specially designed to be used by route guidance algorithms, typically using location data from the GPS system. For example, roads can be described as lines—i.e. vectors (e.g. start point, end point, direction for a road, with an entire road being made up of many hundreds of such segments, each uniquely defined by start point/end point direction parameters). A map is then a set of such road vectors, data associated with each vector (speed limit; travel direction, etc.) plus points of interest (POIs), plus road names, plus other geographic features like park boundaries, river boundaries, etc., all of which are defined in terms of vectors. All map features (e.g. road vectors, POIs etc.) are typically defined in a co-ordinate system that corresponds with or relates to the GPS co-ordinate system, enabling a device's position as determined through a GPS system to be located onto the relevant road shown in a map and for an optimal route to be planned to a destination.
Typically, each such road segment has associated therewith a speed data for that road segment which gives an indication of the speed at which a vehicle can travel along that segment and is an average speed generated by the party that produced the map data. The speed data is used by route planning algorithms on PND's on which the map is processed. The accuracy of such route planning thus depends on the accuracy of the speed data. For example, a user is often presented with an option on his/her PND to have it generate the fastest route between the current location of the device and a destination. The route calculated by the PND may well not be the fastest route if the speed data is inaccurate.
It is known that parameters such as density of traffic can significantly effect the speed profile of a segment of road and such speed profile variations mean that the quickest route between two points may not remain the same. Inaccuracies in the speed parameter of a road segment can also lead to inaccurate Estimated Times of Arrival (ETA) as well as selection of a sub-optimal quickest route. Particularly problematic are jams which may significantly effect the quickest route between two points.
In an effort to improve accuracy it is known to collect live data relating to jammed traffic and to use this data to account for known jams in route planning. It will be appreciated that if the live data is to give a true indication of road conditions a large quantity is required: traffic flow has a strong stochastic component meaning that incident detection based on low levels of or infrequent live data is likely to be inaccurate. It may often be the case, however, that little or no live data is available for a segment and so its true condition may remain unpredictable.